In recent years, enhancement of information security has been strongly desired from a viewpoint of protecting personal information. In particular, biometric authentication technologies such as fingerprint authentication and vein authentication have been attracting attention. This is because disguising a pattern is very difficult in the biometric authentication, and because its resistance to the pattern disguising is superior.
In the pattern matching in which two patterns are determined to belong to the same category or not, there are cases where two patterns that should be determined to belong to different categories are mistakenly determined to belong to the same category. Therefore, in such pattern matching, it is strongly desired to reduce the probability that an incorrect determination is made (false matching rate) below a predetermined value. In other words, it is desired to reduce a false accept rate (FAR), i.e., a rate at which a wrong person is mistakenly accepted, below a predetermined value that is acceptable in the system.
In pattern matching, in general, in order to determine whether two patterns belong to the same category or not, a verification evaluation value such as a distance and the degree of similarity between two patterns is calculated, and then the final determination is made based on a verification result between the verification evaluation value and a determination threshold. When the determination threshold is set to be a strict value, the false matching rate becomes smaller. However, the probability that patterns belonging to the same category are mistakenly determined to belong to different categories becomes higher. When the determination threshold is loosened, the probability that patterns belonging to the same category are mistakenly determined to belong to different categories becomes smaller. However, the false matching rate becomes larger. Therefore, it is necessary to set the determination threshold such that a desired matching accuracy is obtained.
However, when there is no theoretical relation between the verification evaluation value and the false matching rate, it becomes necessary to prepare a database for evaluation, specify a relation between the verification evaluation value and the false matching rate by experiments using the database, and specify a determination threshold.
Non-patent document 1 describes problems that arise when the threshold is obtained experimentally. Non-patent document 1 mentions that when a relation between the verification evaluation value and the false matching rate is obtained as the average performance of data for evaluation by an experiment using a database for evaluation, there are two problems, i.e., variations among each data and database dependence.
The problem of the variations among each data means a problem that the probability of occurrence of false matching varies depending on the data. Even if the average false matching rate is lower than a predetermined value, there is a possibility, depending on data, that there is data for which the false matching rate is higher than the predetermined value. Such data does not satisfy the desired level of safety.
The problem of the database dependence means a problem that when evaluation is made experimentally, the evaluation result depends on the data that was used for the experiment. Data used in an actual operation is different from the data for evaluation. Therefore, if the data depends on the evaluation result, performance in an actual operation cannot be predicted from the result of an evaluation experiment using data for evaluation.
Patent document 1 addresses the problem of variations among each data by defining a threshold for each data by an experiment. In Patent document 2, when matching is to be performed, comparisons with both the data of the person himself/herself and the data of a different person are performed and a verification result is determined based on the degree of similarity of each comparison. By doing so, Patent document 2 addresses the problem of variations among each data.
In Non-patent document 1 and Patent document 3, the false matching rate is theoretically evaluated by using a probability in which feature points match with each other by coincidence. By doing so, Non-patent document 1 and Patent document 3 address both the problem of variations among each data and the problem of database dependence.
Note that Patent documents 4 to 7 also disclose known techniques. Patent document 4 discloses a technique to emphasize ridge lines. Patent document 5 discloses a method and an apparatus capable of performing image matching at a high speed with high accuracy even for an input image in a state where the orientation of an authentication sample or the like is different from the model image. Patent document 6 discloses a technique that enables an input figure to be precisely distinguished even when the input figure is deformed. Patent document 7 discloses a technique that can speed up comparison processing.    [Non Patent Document 1]    “Fingerprint Verification Assuring the Security Strength of Individual Fingerprints” Proceedings of the Symposium on Cryptography and Information Security (SCIS2007), January 2007    [Patent Document 1]    Japanese Unexamined Patent Application Publication No. 2001-21309    [Patent Document 2]    Japanese Unexamined Patent Application Publication No. 2006-18578    [Patent Document 3]    Japanese Unexamined Patent Application Publication No. 2002-288667    [Patent Document 4]    Japanese Unexamined Patent Application Publication No. 9-167230    [Patent Document 5]    Japanese Unexamined Patent Application Publication No. 2001-92963    [Patent Document 6]    Japanese Unexamined Patent Application Publication No. 2002-298141    [Patent Document 7]    Japanese Unexamined Patent Application Publication No. 2005-149455